Definitive Healthcare Corp. (DH) Earnings Call Transcript & Summary

All right. Good afternoon, everyone. Thanks for joining us here for the Definitive Healthcare session. Just as a quick intro, my name is Jared Haase. I worked on the health care IT equity research team here at William Blair. We are excited to be hosting the management team from Definitive here for this session, so a name that we're excited to have here for the first time, a name that we recently initiated coverage on, but I think a really exciting growth story and a really strong value proposition for clients. So I'll let the team go into a little bit more detail here shortly. Just as a couple of quick housekeeping items. I co-cover the name alongside Ryan Daniels who's our senior analyst covering the health care services and IT space. We had double-booked presentations this afternoon, so Ryan's with another company right now. So I get the pleasure of hosting the team. A full list of our compliance disclosures are available at williamblair.com. And in a moment, as I said, the team will run through a detailed presentation. We will have a breakout Q&A session immediately afterwards, and we'll be staying in this room. So we'll be able to just roll right into questions at the conclusion of the presentation. So with that, I'm excited to introduce, at the far end of the table, we have Robert Musslewhite, the company's CEO; and Rick Booth, next to me here, the company's CFO. So with that, I'll turn the mic over to you guys.

Thanks, Jared. Appreciate it. I'm going to stand, as I was told I had both options. So thank you, everybody, for coming to our presentation, and thanks to William Blair for hosting us. I was thinking back, I don't think I've been at the conference since 2017 and I was with another organization, but the coverage has always been great. Ryan and Jared do a fantastic job, so I encourage you to continue to look at what they say about us because they did a nice job covering us. And I see some old friends in the audience, so welcome to Definitive. I'm going to just go through a few key things here, and this is why you should be interested in listening to the rest of the presentation. I came to Definitive, I joined the company a little under 2 years ago. I stepped into this role a little under a year ago, last August. And there are so many things I love about the business. We've tried to distill them into the things that matter the most for you guys here but, obviously, happy to answer any questions as we get through the presentation. Number one is we've really defined the category of health care commercial intelligence. We have a very easy-to-use, valuable software platform that makes it easy for anybody who sells into health care, wants to grow within health care, wants to target individuals or facilities within health care and a bunch of analytics around that and make it very easy for clients to use. That is our core value proposition, health care commercial intelligence, and it's delivered through a really easy-to-use SaaS platform. And that gets to number two. There's a huge TAM for what we do. It's a $10 billion-plus growing TAM across multiple different end markets. And we believe that, from where we are today which is kind of mid-200s in revenue, there's significant expansion opportunities from where we are today to continue to penetrate that TAM. Rick likes to say we're in the early innings of a huge market opportunity, very early innings. Third, we apply a very sophisticated health care AI engine and a lot of analytics, which make formidable competitive moat against others. So there's a lot of use and value cases for our clients that we provide that others can't based on the data that we have. And then over time, we have this innovation flywheel where we keep running analytics on our own data, so we create metadata and new data elements that are distinctive and they continue to deliver new value to clients. I'll talk a little bit about more as we go through that, but I'll show you an example of that. That compounds the strength of this platform that we have. Fourth, we deliver our product by a mission-critical SaaS platform, which is deeply embedded in the customer workflow. It's designed to be really easy for clients who want to get the value from the data very quickly. So a client can sign on the next day or next hour, we can turn on their site. It's very easy to them to navigate to the data they need, to pull the data they need. They can export the data they need. Some clients choose to integrate the data. Most of our clients choose to integrate the data with their own source systems, whether that's internal data warehouses or their CRM system. We like that because it makes our data more valuable to them. It gets it embedded in their daily workflow, and it makes it stickier. Fifth, a demonstrated combination of high growth and high profitability. We'll talk about that a lot. We focus on both. The company has been profitable from day 1. We have always focused on balancing smart growth investments with delivering a strong bottom line for our investors. So you'll see at scale Rule of 40 financials continuing into the future. And then an experienced management team, I didn't write this one, but I guess I count sort of in this. But we do have a good management team. The team took the company through the IPO in September of 2021. A lot of our management team and [ Nextel ] management team have been with the company for a long time. They know the products really, really well. They know our customers. They know our markets. It's a team that really knows how to continue to innovate around this space. So those are the things we'll talk about. And again, happy to answer any questions at the end. If I jump in to our platform, this is a very easy way to think about what we do for clients. We deliver our intelligence through a SaaS-based platform. 98% of our revenue is subscription-based. Clients tend to sign on for multiyear contracts. What it helps them do through this platform is drive commercial success in health care, so sales, marketing, clinical research, product development, strategy, M&A, physician network management, talent acquisition, those are all really common use cases among our clients. And then we do that across the entire continuum of health care. So life sciences, health care IT providers and other diversified, it's really anybody who has an interest in selling into health care, including people in the industry themselves. So that's what the platform does and the types of clients we serve. Here's an example of just the types of value proposition we provide. A lot of people out there who might sell lists of contacts or kind of a really thin layer across all industries, we go really deep within health care to help answer questions around sales and marketing, around product development, around network development. So people can plan how they target their reps and where their reps should go, and then people can understand what the market is for a certain product and how they might best position their product against competitors or who they should target for that particular product. Network development. Health systems can target which physicians they want. They can look at performance across different physician networks. They can look at patient flow across networks and see if patients are leaking or referrals are being made out of network. So really along the bottom here, you can see sales, marketing, same use case I listed on the prior page, that is significant ROI from using our product. So why are we so distinctive? We get asked a lot, like "What's the distinctiveness of this platform?" It seems like great use cases. We understand the ROI. It starts with our data. And our data has been something that we've worked on repeatedly with a lot of time and energy over 12 years. The company started with first-party data research collection. I mean Jason Krantz, our Founder's concept was, "How do I build a map of the complex health care ecosystem that's going to make it easier for people who want to be commercially successful in health care?" It started with already a lot of first-party research when the company was founded. And we still continue that today. We do over 4 million interactions every year that includes phone calls, e-mail outreach, survey outreach into the market. We use data science to target where that outreach is most likely to be needed to update our data or to acquire new data to build on the platform. But that's been running over a long period of time. That's stuff that's very proprietary to us. We also pull in unstructured public information so we can scrape a bunch of websites for information that's likely to be relevant. We aggregate everything around one Definitive ID that's assigned to any individual in the health care or any facility, in any facility. So we'll pull that information and aggregate it around the right nodes. We do pull in a lot of government and regulatory agency data. There's a lot of great data we can get there. Some of it lags, some of it more current. But in general, that stuff is really important to building out the whole perspective on the health system. And then only in recent years did we start buying some third-party data. And think of that as mostly claims data. We started with medical claims and have a really strong position in medical claims today, and then prescription claims where we're still building our presence but have really good coverage. And the nice thing is we can also match a medical claim with a prescription claim at the physician level. So we have a lot of use cases that are around tracking patient journey across physicians because we can aggregate that data. And that's the second step is the innovation flywheel around this data. We pull in data from all these sources. We've gotten very good at cleaning it, deduping it, pulling it together, aggregating around this Definitive Healthcare ID, linking it. And then importantly, what I mentioned before, is running data science on our own data. So we've created several new data elements, which I'll talk about a little bit, that just come from running data science on our own data. But in general, that creates our data set in the middle. And obviously, we have a lot of people who are really good at doing that kind of work with a lot of subject matter expertise. They've been doing it for a long time. And then that creates the real map. And within the data, you now have fully accurate insight into all the linkages across the health system. And what's interesting is, if you think about somebody selling something like a knee replacement, like artificial joint, there's actually not one entity on the right that's the actual sole buyer for that knee. You need to know which physicians are most likely to be the highest users of that knee. And you need to know which physician network they're part of, and then you need to know who makes purchasing decisions for that physician network, and you need to know the volume across that purchaser's domain. Is it the health system? Is it the physician group entity? Is there a geographic cut? And then you need to know who they're using today and is there a market share shift they're going after. If you're going to go in and get one shot at being successful with that sale, you better know all those linkages and understand those relationships and the facts behind them to make the most effective sales pitch. So again, this intelligence is extremely valuable for people's sales, marketing and growth efforts within health care. How do we think about growth? Pretty simple. There's 4 ways. I feel like I showed this slide from Advisory Board days as well, but it's pretty simple. We go out and acquire new customers. We have 3,000 customers today. We have a universe of 100,000 potential customers. So we're always adding new customers. Second, once we get them on board, we look to land and expand. Today, the average customer spends about $70,000 with us. But we have more than 10 $1 million customers today, 1 over $3 million, and we had none of those 3 years ago. So the potential to continue to expand across our user base is really, really high. Third, we do a ton of innovation every year. And I'll talk about some of the innovations that we've already announced this year. But there's a lot of innovation. Sometimes, that will be a new product that we'll sell separately. But a lot of times, it's to strengthen our data and strengthen our platform to increase this core value proposition that continues to drive long-term subscription and long-term value for clients. And then finally, I'll talk about selective strategic acquisitions. We've talked about doing roughly 1 to 2 acquisitions per year. They tend to be tuck-in. And I'll talk about those criteria a little bit later, but these are all the growth levers that kind of drive the formula for long-term sustainable growth. So acquiring new customers. I'm not going to go through all the detail here, but what's cool here, as you think about what we can offer, someone who's selling, this is a software device around knee replacement. So it's kind of a device that can be used to target and help make a new replacement effective. But number one, you can size the market. So someone can come to us and say, "How big is the market for this product if I'm going to roll it out?" We can map the decision-making entity, so who should you be targeting to maximize commercial success. We can then quantify the ROI around the product to be sure that when you walk in -- and again, like in-person interactions are down. If you're going to get a chance to go meet someone in person and make a sales pitch, sometimes you get one shot. We can crystallize the ROI and messaging, make sure you walk in with all the facts around how many procedures they're looking at today, how many people are involved, what the upside is from switching to your products. And finally, we can provide specific contact information to access the decision-maker you want to reach and which decision-maker is most relevant. So a lot of value just for a pretty simple use case, and that's all within a few clicks within our product. No one has to help them do that. You turn it on, click, click, click, you have all the information. Once we have someone onboard, this tends to look like most of our customer profiles. So we bring them on in a small ARR. They see value from us. They expand that ARR the next year. Each year in succession, we're coming back to them, talking about the value we're creating and adding on new ways for them to expand. That can be through expansions of the data sets they buy. It can be expansions of the use cases they serve. It can be expansion in seats. But there are lots of ways we tend to grow client relationships. And if you look at the dynamics in our business, our largest customers have the highest NDR. Our largest customers renew at the highest rates. That makes sense because they've tended to go through this process, see the value over time and built on their value relative to a really small client that sometimes has a little more tendency to come in and out. So you see the strength in the business as people become large clients and become stickier. By the way, I think this is within one therapeutic area, this specific example. So for life science clients, in particular, we're still pretty early days of building these types of relationships. So we tend to be within 1 TA or one brand. And if you look at this size, this is a medium size within one brand, it could be $2 million to $3 million within a brand, and then there are multiple brands per life science company, you can see how we have a big belief in the expand part of our value proposition. Innovation. We're always announcing releases. So you'll see us do a lot of press releases around what we're doing. This year, we've already announced 3. The first was our Atlas Dataset. This was a little bit of a marketing announcement because we were remarketing the distinctiveness of our data, but we also announced significant additions to our medical claims and our prescription claims. We basically brought 2 new sources online and expanded our coverage dramatically in medical claims and in prescription claims. We covered a lot of really important rare disease areas, strengthened our oncology coverage and things like that, which really matter to our clients. So that's exciting. We also were able to talk about some statistics around the Atlas Dataset, such as we're #1 ranked for our use cases around reference and affiliation data, which is great to know. We can market that externally. We can have our salespeople go out and talk about the 4 components of the Atlas Dataset, which is the core Atlas Reference & Affiliation data, the Atlas All-Payor medical claims, the Atlas Prescription Claims and the Atlas Experts data. That's a great way for our salespeople to get back in front of an audience and talk about how distinctive we are. I'm going to go to the far right because this is the order of our announcements. We announced integrations also, and that's really important to our clients. Remember, I talked earlier about how a lot of clients like to take our data and integrate it into their Salesforce instance. Well, we made it easier with upgrading our ability to pull data into Salesforce through their platform. We're now able to have clients access our data through Snowflake. And we announced a new set of APIs that make it even easier than the ones we had before for people to take the data and just pull it into their Salesforce instance or their CRM instance. So that's been really great. Clients love that. The uptake on that and the reaction to that has been high. We love it when people want to integrate their data. We do upcharge for that. But it's a win-win because if clients use it, it's better for us, too. And then on the Atlas AI side, we just made that launch. That's been our most recent launch. And really, again, this had components of new and components of marketing existing a little better. But this reflects what I talked about earlier, is that we embed a lot of data science and AI into our own data set where we are analyzing and running models on our own data and then creating new data sets. So the one I'd love to talk about here, we listed some other ones here, but we had clients that would say, "Okay, we want to target the right physician for our product." It's a drug company, same one targeted by physicians. We can cut that by volume and say, "Here are the highest prescribers of your drug class," "Here's where they're located," "Here's ones that prescribe your drug," "Here's ones that subscribe your competitor's drug." That's all helpful. But what we can also do is say, "Hey, if you have limited resources with limited time and you want to allocate your salespeople's time and budget against the most important physicians, how can we define most important for you?" Well, one way we can define it is who's most likely to influence a lot of others if they switch. So if you can switch this guy right here, [ Malithan ]. If you can switch [ Malithan ], will others follow? Or if you can switch Rick Booth, fewer will follow. So we can create a prescribing influencer score and, therefore, deliver that as part of our data elements. People can just go in and say, "Well, hey, this person might have lower volume. But this person, if they prescribe differently, will get a big follow-on effect." For whatever reason, that person's a leading thought leader in the space. That person controls their formulary. That person has a high influence in their colleagues and peers, in their same institution, whatever. It doesn't really matter. But we know that those are more likely to have a follow-on influence. So things like that, we do all the time. We load them into our data set. They're super valuable to our clients. They love them. We also do a lot of AI to be sure. Like, this [ ACE ] projections, if you have data, you'll generally cover the majority of the market, a very high majority of the market. But sometimes in certain markets you have to fill in, we do a great job of using AI to model in, to complete out those markets. And the feedback we get is that we do that better than others. So if someone wants to have accurate market data, no one has exact 100% full claims coverage of everything, but we can do a really nice job of building that out based on our AI. So that's just this year, and we're always going to be doing more of this, and we'll keep announcing them. And then finally, on M&A, what we tend to look for, I'd say our strategy has been tuck-in. And we look for smaller companies that are growing quickly with a unique product or service or capability that we can pull in and sell broadly across our sales force. If they have data, we can load the data into our data set and have it be something that becomes part of the power of our data set. In many cases, our data can make the acquired company's solutions stronger. And I'll talk about a couple in a second. These companies tend to be $5 million to $25 million in revenue, growing quickly. They tend to be losing money. But we want to look for economics that we can get to breakeven relatively quickly, within a year or 18 months, and get them to our margins pretty quickly after that or approaching our margins. So that's how we look at it. We acquired a company called Monocl back in 2020. That's a key opinion leader. It was one of the leaders in having key opinion leader data or expert data. It's now the foundation of our Atlas Experts data. It's been a fantastic solution. What's great there is they have millions of -- or hundreds of thousands of individuals. And all their sort of affiliations with publications, their university relationships, the papers they've written, where they practice, we've been able to aggregate that with all the people that we had in our database and now have a whole expert component to the data we can provide to a buyer of our services. That's been a great growth story for us. It helps us serve medical affairs, helps us serve clinical trial development use cases. So we get a little bit further upstream in the commercialization process, and we continue to build around that with our service to medical affairs people and biopharma companies. Analytical Wizards, we acquired just a little over a year ago. They didn't have data, but they had a powerful analytics platform. And what they're great at doing is taking whatever data is out there, the client's data, our data, someone else's data, and creating really easy-to-use, really quick-to-develop analytics and then having a standardized delivery of those analytics over time. So they're able to do pretty complex analytics at a lower price point than a consulting firm would do for clients who want the data sort of cut and analyzed in a certain way. It's been really nice for us because we can walk in the door. And if they don't happen to use Definitive data yet, we can still sell. We call it Passport Analytics now, we can still sell Passport and then use that over time to get in with that client and build over time, like you saw in the prior chart, of building over time. It's also been something where we have preloaded our data into their analytics across 20 therapeutic areas, and we sell that as a Passport Analytics product. And so that's really cool. So within 6 months, we have their analytics, which are really easy to use with our data preloaded into it. And it's basically an off-the-shelf complex analytics product for biopharma companies. So that's been really exciting. And we've said we'll continue to look for these on the pace of 1 or so per year. It's been a little over a year, but private valuations have been a little tough in the past year. Hopefully, they're starting to adjust, and I do think we'll stay back on that pace. So with that, I'll turn it over to Rick to walk through a few of the numbers and then we'll take questions.

Well, thank you very much for the intro, Robert. I joined this company for one simple reason Well, thank you very much for the intro, Robert. I joined this company for one simple reason: the financial model is a thing of beauty. We're growing into a large TAM, a $10 billion TAM, that's growing every year with secular long-term trends around the increased digitization of health care information. That's a big enough field for us to play in. We're still relatively small. We're targeting mid-250s growth next year. So we're just getting started. We have the ability to grow through new logos as well as through upsell and acquisition. I like optionality, so that was very attractive to me. And we're highly profitable. Our gross margins are in the mid- to high-80% range. They've been as high as in the 90% range, within recent history. But incrementally, every dollar that we add is very powerful. We've chosen to make some investments, since going public, primarily in sales and marketing and in G&A because who doesn't love G&A. We're already realizing scale from our G&A investments, and we're confident that we will over time from sales and marketing. And Robert mentioned the innovation flywheel. We're able to drive this growth with roughly 12% development spend, which we're really proud of because the more data that we append into our proprietary data set, the more valuable it becomes. We have a really efficient sales and marketing engine. Current headwinds are obscuring that a little bit, but still very strong. And then finally, because I've been doing this for a long time, I value visibility and consistency. 98% subscription revenue, primarily long-term contracts and very low CapEx, means that I sleep well at night knowing that you sleep well at night. So that's what attracted me here. Another thing that I like about it is that we deliver both attractive growth and attractive profitability. And we view that day in, day out. Fashions on Wall Street change, but our investment philosophy doesn't. Jason Krantz, our founder, launched this business right into the teeth of the 2008 recession. So he said it was the best decision of his life that felt like the worst decision of his life. So from day 1, we've inculcated a scrappy culture in which we measure everything, and we adjust as we see appropriate. You saw this recently. We were among the first to call out the deteriorating economic conditions for enterprise software back in Q2. We've stayed on top of that and we continue to provide updates each period. And over time, we'll continue to deliver this combination of growth and profitability. And then we're not here to provide any updates on conditions post Q1 just because that would be material nonpublic information that none of us wants. But just for your reference, in this presentation that you see in your conference application, that gives you a sense of our guidance this year. So we're coming off of a year in which we grew total revenue 33%. 27% of that growth was organic. We're facing some industry headwinds, as we have talked about in our guidance, which means that we're guiding towards mid-teens growth this year, continuing to deliver strong profitability. And with that, I would be happy to expand on any of it, but I know that this is a generalist conference. And so I wanted to let us get to questions. And to the extent that you're intrigued, you can always reach out to us later. [Audio Gap]